Comparison of the composition and metabolic potential of the reindeer’s rumen microbiome in the Yamal-Nenets and Nenets autonomous district of the Russian Arctic - E. S. Ponomareva; E. A. Yildirim; V. A. Filippova; L. A. Ilina; A. V. Dubrowin; G. Y. Laptev; K. A. Kalitkina; T. P. Dunyashev; D. G. Tiurina (Acta Biomedica Scientifica, 2022)
The adaptive ability of reindeer to the harsh conditions of the Russian Arctic is not determined solely by the genome of the macroorganism and, of course, includes an extensive genetic and metabolic repertoire of the microbiome.The aim. To compare the taxonomic and predicted metabolic profiles of the rumen microbiome of adult reindeer living in the natural pastures of the Yamalo-Nenets and Nenets Autonomous districts of the Russian Federation.Materials and methods. Expeditions to the Yamal-Nenets and Nenets Autonomous districts of the Russian Arctic in 2017 were carried out to take samples of the rumen. The contents of the rumen were taken from clinically healthy reindeer individuals (at least 3 times repetition). To analyze the animal scar microbiota and determine metabolic profiles, 16S rRNA NGS sequencing was performed on a MiSeq device (Illumina, USA). Bioinformatic data analysis was performed using QIIME2 software ver. 2020.8. The noise sequences were filtered by DADA2. Silva 138 reference database was used for taxonomy analysis. Reconstruction and prediction of the functional content of the metagenome was carried out using the software complex PICRUSt2 (v. 2.3.0).Results. During NGS sequencing, a total of 223 768 sequences of the 16S rRNA gene of the reindeer scarring microbiome were studied. Significant (p ≤ 0.05) differences between the groups in 10 bacterial phyla and superphyla were revealed: Actinobacteriota, Spirochaetes, Chloroflexi, Verrucomicrobia, Bdellovibrionota, Synergistetes, Fusobacteriota, Myxococcota, Cyanobacteria, Campilobacterota. The results of the reconstruction and prediction of the functional content of the metagenome using the PICRUSt2 bioinformatic analysis made it possible to identify 328 potential metabolic pathways. Differences between the groups were revealed in 16 predicted metabolic pathways, among which the pathways of chlorophyllide and amino acid biosynthesis dominated.